Systems Biology of Reproduction Discussion Outline (Systems Biology) Michael K
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Spring 2020 – Systems Biology of Reproduction Discussion Outline (Systems Biology) Michael K. Skinner – Biol 475/575 Weeks 1 and 2 (January 23, 2020) Systems Biology Primary Papers 1. Westerhoff & Palsson (2004) Nat Biotech 22:1249-1252 2. Joyner (2011) J Appl Physiol 111:335-342 3. Clarke, et al. (2019) Endocr Relat Cancer. 26(6):R345-368 Discussion Student 1 - Ref #1 above -How does this support evolutionary systems biology? -What was the convergence discussed? -Give an example that supports this perspective. Student 2 - Ref #2 above -What is the problem with reductionism? -What is the void? -What is the solution? Student 3 - Ref #3 above -What is multiscale modeling? -What is the role of mathematical modeling? -What network analysis insights into endocrine cancers are described? HISTORICAL PERSPECTIVE The evolution of molecular biology into systems biology Hans V Westerhoff1 & Bernhard O Palsson2 Systems analysis has historically been performed in many high-throughput technologies—more emphasis is placed on the sec- areas of biology, including ecology, developmental biology ond root, which sprung from nonequilibrium thermodynamics theory and immunology. More recently, the genomics revolution in the 1940s, the elucidation of biochemical pathways and feedback has catapulted molecular biology into the realm of systems controls in unicellular organisms and the emerging recognition of net- biology. In unicellular organisms and well-defined cell lines works in biology. We conclude by discussing how these two lines of of higher organisms, systems approaches are making definitive work are now merging in contemporary systems biology. strides toward scientific understanding and biotechnological applications. We argue here that two distinct lines of inquiry Scaling-up molecular biology in molecular biology have converged to form contemporary In the decades following its foundational discoveries of the structure systems biology. and information coding of DNA and protein, molecular biology blos- http://www.nature.com/naturebiotechnology somed as a field, with a series of breathtaking discoveries (Fig. 1). The Whereas the foundations of systems biology-at-large are generally rec- description of restriction enzymes and cloning were major break- ognized as being as far apart as 19th century whole-organism embryo- throughs in the 1970s, ushering in the era of genetic engineering and logy and network mathematics, there is a school of thought that biotechnology. In the 1980s, we began to see the scale-up of some of systems biology of the living cell has its origin in the expansion of the fundamental experimental approaches of molecular biology. molecular biology to genome-wide analyses. From this perspective, the Automated DNA sequencers began to appear and reached genome- emergence of this ‘new’ field constitutes a ‘paradigm shift’ for molecu- scale sequencing in the mid-1990s4,5.Automation, miniaturization lar biology, which ironically has often focused on reductionist think- and multiplexing of various assays led to the generation of additional ing. Systems thinking in molecular biology will likely be dominated by ‘omics’ data types6,7. formal integrative analysis going forward rather than solely being The large volumes of data generated by these approaches led to driven by high-throughput technologies. rapid growth in the field of bioinformatics, again largely emanating It is, however, incorrect to state that integrative thinking is new to from the reductionist perspective. Although this effort was mostly molecular biology. The first molecular regulatory circuits were focused on statistical models and object classification approaches in © 2004 Nature Publishing Group mapped out over 40 years ago. The feedback inhibition of amino acid the late 1990s, it was recognized that a more formal and mechanistic biosynthetic pathways was discovered in 1957 (refs. 1,2), and the tran- framework was needed to analyze multiple high-throughput data scriptional regulation associated with the glucose-lactose diauxic shift types systematically8,9.This need led to efforts toward genome-scale led to the definition of the lac operon and the elucidation of its regula- model building to analyze the systems properties of cellular function. tion3.With the study of these regulatory mechanisms, admittedly on a small scale, molecular biologists began to apply systems approaches to Molecular self-organization unravel the molecular components and logic that underlie cellular Even before the first key events in the history of molecular biology, processes, often in parallel with the characterization of individual several lines of reasoning revealed that integration of multiple molecu- macromolecules. High-throughput technologies have made the scale lar processes is fundamental to the living cell. Biochemical processes of such inquiries much larger, enabling us to view the genome as the necessitate the production of entropy (chaos in the thermodynamic ‘system’ to study. Thus, the popular contemporary view of systems sense) as driving force. The paradox felt by many, but expressed by biology may be synonymous with ‘genomic’ biology. Schrödinger in his war-time lectures10, was how one could explain This article discusses two historical roots of systems biology in the progressive ordering that occurs in developmental biology (that is, molecular biology (Fig. 1). Although we briefly outline the more the ‘self-organization,’decrease in chaos) when entropy (‘chaos’) must familiar first root—which stemmed from fundamental discoveries be increased. about the nature of genetic material, structural characterization The answer was that one process could produce order (negative of macromolecules and later developments in recombinant and entropy or negentropy) provided it was coupled to a second process that produced more chaos (entropy): coupling, another word for inte- gration of processes, is therefore essential for life. Onsager11 provided 1 Departments of Molecular Cell Physiology and Mathematical Biochemistry, the basis for this concept by stressing the significance of the coupling BioCentrum Amsterdam, De Boelelaan 1085, NL-108, HV Amsterdam, the Netherlands. 2Department of Bioengineering, University of California-San Diego, of dissimilar processes. He is also relevant because he discovered a law 9500 Gilman Drive, La Jolla, California 92093-0412, USA. Correspondence for such systems of coupled processes: close to equilibrium the should be addressed to H.V.W. ([email protected]) or B.O.P. ([email protected]). dependence of the one process rate on the driving force of the other Published online 6 October 2004; doi:10.1038/nbt1020 process should equal the dependence of the other process rate on the NATURE BIOTECHNOLOGY VOLUME 22 NUMBER 10 OCTOBER 2004 1249 HISTORICAL PERSPECTIVE Haemophilus influenzae Recombinant first genome DNA the Automated technology sequenced Human genome sequencing genetic DNA sequenced material structure 1995 2001▲ 1944 1953 1960 1970 1980 1990 2000 High-throughput at genome scale, 'data rich' biology ▲ Systems analysis critical to molecular biology ‘Data poor’ in silico biology, ▲ Feedback regulation models of viruses, in metabolism red blood cell 1931 1952 1957 1970 1980 1990 2000 ▲ Non-equilibrium Self- thermodynamcs organization Large-scale simulators Genome-scale models of metabolic dissipative and analysis, large-scale structures, energy coupling kinetic models http://www.nature.com/naturebiotechnology Analog simulation, MCA and BST bioenergetics, lac operon Erin Boyle Figure 1 Two lines of inquiry led from the approximate onset of molecular biological thinking to present-day systems biology. The top timeline represents the root of systems biology in mainstream molecular biology, with its emphasis on individual macromolecules. Scaled-up versions of this effort then induced systems biology as a way to look at all those molecules simultaneously, and consider their interactions. The lower timeline represents the lesser-known effort that constantly focused on the formal analysis of new functional states that arise when multiple molecules interact simultaneously. former driving force. Caplan, Essig and Rottenberg12 later defined a environment, a phenomenon called symmetry breaking. Turing16 led coupling coefficient, which quantifies the extent to which two the way, but the Prigogine school17 and others developed the topic processes are coupled in a system and showed that this coefficient from the perspective of nonequilibrium thermodynamics in molecu- © 2004 Nature Publishing Group must range between 0 and 1. lar contexts such as biochemical reactions involved in sugar meta- These approaches were called nonequilibrium thermodynamics and bolism (glycolysis). They demonstrated how having a sufficient number constituted a prelude to systems biology at the cell and molecular lev- of nonlinearly interacting chemical processes in a single system such as els in that they (i) dealt with integration quantitatively and (ii) aimed the Zhabotinski reaction, a developing tissue, or glycolysis, could lead to discover general principles rather than just being descriptive. An to symmetry-breaking as a result of self-amplification of random improved procedure for describing ion movement and energy trans- fluctuations. Of course, more recent molecular developmental biology duction in biological membranes, termed mosaic nonequilibrium studies have shown that reality is even more complicated; pre- thermodynamics, further progressed towards systems thinking in specification